Evidence from a broad panel of countries shows little overall relation between income inequality and rates of growth and investment. However, for growth, higher inequality tends to retard growth in poor countries and encourage growth in richer places. The Kuznets curve—whereby inequality first increases and later decreases during the process of economic development—emerges as a clear empirical regularity. However, this relation does not explain the bulk of variations in inequality across countries or over time.

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We study the effect of the level of inequality in society on individual well-being using a total of 123,668 answers to a survey question about ‘‘happiness’’. We find that individuals have a lower tendency to report themselves happy when inequality is high, even after controlling for individual income, a large set of personal characteristics, and year and country (or, in the case of the US, state) dummies. The effect, however, is more precisely defined statistically in Europe than in the US. In addition, we find striking differences across groups. In Europe, the poor and those on the left of the political spectrum are unhappy about inequality; whereas in the US the happiness of the poor and of those on the left is uncorrelated with inequality. Interestingly, in the US, the rich are bothered by inequality. Comparing across continents, we find that left-wingers in Europe are more hurt by inequality than left-wingers in the US. And the poor in Europe are more concerned with inequality than the poor in America, an effect that is large in terms of size but is only significant at the 10% level. We argue that these findings are consistent with the perception (not necessarily the reality) that Americans have been living in a mobile society, where individual effort can move people up and down the income ladder, while Europeans believe that they live in less mobile societies.

The Difference and System generalized method of moments (GMM) estimators are growing in popularity, thanks in part to specialized software. But as implemented in these packages, the estimators easily generate results by default that are at once invalid yet appear valid in specification tests. The culprit is their tendency to generate instruments that are a) numerous and, in System GMM, b) suspect. A large collection of instruments, even if individually valid, can be collectively invalid in finite samples because they overfit endogenous variables. They also weaken the Hansen test of overidentifying restrictions, which is commonly relied upon to check instrument validity. This paper reviews the evidence on the effects of instrument proliferation, and describes and simulates simple ways to control it. It illustrates the dangers by replicating two early applications to economic

Abstract—The extent to which growth reduces global poverty has been disputed for 30 years. Although there are better data than ever before, controversies are not resolved. A major problem is that consumption measured from household surveys, which is used to measure poverty, grows less rapidly than consumption measured in national accounts, in the world as a whole and in large countries, particularly India, China, and the United States. In consequence, measured poverty has fallen less rapidly than appears warranted by measured growth in poor countries. One plausible cause is that richer households are less likely to participate in surveys. But growth in the national accounts is also upward biased, and consumption in the national accounts contains large and rapidly growing items that are not consumed by the poor and not included in surveys. So it is possible for consumption of the poor to grow less rapidly than national consumption, without any increase in measured inequality. Cur-rent statistical procedures in poor countries understate the rate of global poverty reduction, and overstate growth in the world. I.

This paper draws on the experience of the 1970-95 period to (1) elucidate some of the main causes of child malnutrition in developing countries; (2) undertake projections of how many children are likely to be malnourished in the year 2020 given current trends; and (3) identify priority actions for reducing malnutrition the most quickly in the coming decades. The analysis is based on country fixed-effects multivariate regression using data from 63 countries. The paper finds four "underlying" determinants to be key factors: health environments, women's education, women's relative status, and per capita food availability. Two "basic" determinants are also found to be important: per capita national incomes and democracy. Due to data scarcities, the role of poverty could not be assessed. Improvements in women's education was found to have contributed the most to past reductions in child malnutrition. For Sub-Saharan Africa and South Asia---the regions with the highest child malnutrition rat...

We estimate the WDI by integrating individual income distributions for 138 countries between 1970 and 2000. Country distributions are constructed by combining national accounts GDP per capita to anchor the mean with survey data to pin down the dispersion. Poverty rates and headcounts are reported for four specific poverty lines. Rates in 2000 were between one-third and one-half of what they were in 1970 for all four lines. There were between 250 and 500 million fewer poor in 2000 than in 1970. We estimate eight indexes of income inequality implied by our world distribution of income. All of them show reductions in global inequality during the 1980s and

The premise of neo-classical growth theory is that it is possible to do a reasonable job of explaining the broad patterns of economic change across countries, by looking at it through the lens of an aggregate production function. The aggregate production function relates the total output of an economy (a country, for example) to the aggregate amounts of labor, human capital and physical capital in the economy, and

We estimate the world distribution of income by integrating individual income distributions for 125 countries between 1970 and 1998. We estimate poverty rates and headcounts by integrating the density function below the $1/day and $2/day poverty lines. We find that poverty rates decline substantially over the last twenty years. We compute poverty headcounts and find that the number of one-dollar poor declined by 235 million between 1976 and 1998. The number of $2/day poor declined by 450 million over the same period. We analyze poverty across different regions and countries. Asia is a great success, especially after 1980. Latin America reduced poverty substantially in the 1970s but progress stopped in the 1980s and 1990s. The worst performer was Africa, where poverty rates increased substantially over the last thirty years: the number of $1/day poor in Africa increased by 175 million between 1970 and 1998, and the number of $2/day poor increased by 227. Africa hosted 11 % of the world’s poor in 1960. It hosted 66 % of them in 1998. We estimate seven indexes of income inequality implied by our world distribution of income. All of them show substantial reductions in global income inequality during the 1980s and 1990s.

Research on inequality and growth can be divided into two strands. One, deriving from Kuznets and Lewis, has tried to identify a mechanistic relationship between growth and inequality. The other has tried to find causal explanations of growth and inequality, treating them independently. In this paper, we draw from both strands to test whether growth and inequality are the joint outcomes of other variables and processes. We find that simultaneous examination of growth and inequality yields significantly different results, and has different consequences for policy, than previous independent studies. We also examine the determinants of growth among different income classes. We find that the disaggregated analysis clarifies and extends the results of the aggregate analysis, especially concerning the impact of globalization on the poor.